<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>hanseul0618.r-universe.dev</title><link>https://hanseul0618.r-universe.dev</link><description>Recent package updates in hanseul0618</description><generator>R-universe</generator><image><url>https://github.com/hanseul0618.png</url><title>R packages by hanseul0618</title><link>https://hanseul0618.r-universe.dev</link></image><lastBuildDate>Thu, 28 May 2026 17:07:25 GMT</lastBuildDate><item><title>[hanseul0618] rwetools 0.1.2</title><author>hanseul0618@gmail.com (Hanseul Cho)</author><description>Toolbox that provides a streamlined, end-to-end workflow
for propensity score analysis in generating real-world evidence
from real-world data. The package covers the full analytic
pipeline - from estimating propensity scores via logistic
regression, to calculating weights or creating a matched
cohort, to generating publication-ready Table 1s with
standardized mean differences and weighted balance diagnostics.
It also estimates incidence rates, hazard ratios, risk ratios,
and risk differences with support for stratified and
direct-standardized analyses. All core functions produce
formatted 'Excel' reports with embedded 'README' documentation,
making results immediately shareable with collaborators and
stakeholders. Methods are based on Rosenbaum and Rubin (1983)
&lt;doi:10.1093/biomet/70.1.41&gt;, Austin (2011)
&lt;doi:10.1080/00273171.2011.568786&gt;, and Desai et al. (2017)
&lt;doi:10.1097/EDE.0000000000000595&gt;.</description><link>https://github.com/r-universe/hanseul0618/actions/runs/26625915296</link><pubDate>Thu, 28 May 2026 17:07:25 GMT</pubDate><r:package>rwetools</r:package><r:version>0.1.2</r:version><r:status>success</r:status><r:repository>https://hanseul0618.r-universe.dev</r:repository><r:upstream>https://github.com/cran/rwetools</r:upstream></item></channel></rss>